Effectiveness of Apparent Diffusion Coefficient Values in Predicting Pathologic Subtypes and Grade in Non-Small-Cell Lung Cancer

Abstract

Background and Objective: The aim of this study is to evaluate the effectiveness of apparent diffusion coefficient (ADC) values in predicting pathologic subtypes and grade in non-small-cell lung cancer (NSCLC). Materials and Methods: From January 2018 to March 2020, 48 surgically diagnosed NSCLC cases were included in this study. To obtain ADC values, ADC maps were constructed, and a region of interest was put on the tumor. The values were measured three times from different places of the lesion, and the mean value of these measurements was recorded. All MRI scans were evaluated by two radiologists in consensus. Results: A total of 14 cases were squamous cell cancer, 32 cases were adenocarcinoma, and 2 cases were large cell carcinoma. The mean ADC values of adenocarcinoma, squamous cell carcinoma, and large cell cancer were 1.51 ± 0.19 × 10−3 mm2/s, 1.32 ± 0.15 × 10−3 mm2/s, and 1.39 ± 0.25 × 10−3 mm2/s, respectively. There were 11 grade 1, 27 grade 2, and 10 grade 3 NSCLC cases. The mean ADC value was 1.44 ± 0.14 × 10−3 mm2/s in grade 1 tumors, 1.25 ± 0.10 × 10−3 mm2/s in grade 2 tumors, and 1.07 ± 0.15 × 10−3 mm2/s in grade 3 tumors. The cut-off value to discriminate grade 2 from grade 1 tumors was 1.31 ± 0.11 × 10−3 mm2/s (85% sensitivity, 75% specificity). The cut-off value to discriminate grade 3 from grade 2 tumors was 1.11 ± 0.15 × 10−3 mm2/s (87% sensitivity, 69% specificity). Conclusions: ADC values can accurately predict NSCLC histopathologic subtypes and tumor grade.

Keywords

• non-small-cell lung cancer
• diffusion-weighted imaging
• ADC value
• tumor grade
• squamous cell lung cancer
• lung adenocarcinoma